{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T02:07:49Z","timestamp":1771466869034,"version":"3.50.1"},"reference-count":30,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,23]],"date-time":"2021-12-23T00:00:00Z","timestamp":1640217600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003246","name":"Dutch Research Council","doi-asserted-by":"publisher","award":["project P16-05"],"award-info":[{"award-number":["project P16-05"]}],"id":[{"id":"10.13039\/501100003246","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100019926","name":"Netherlands Organisation for Applied Scientific Research","doi-asserted-by":"publisher","award":["i-Botics Early Research Program"],"award-info":[{"award-number":["i-Botics Early Research Program"]}],"id":[{"id":"10.13039\/501100019926","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The risk of low-back pain in manual material handling could potentially be reduced by back-support exoskeletons. Preferably, the level of exoskeleton support relates to the required muscular effort, and therefore should be proportional to the moment generated by trunk muscle activities. To this end, a regression-based prediction model of this moment could be implemented in exoskeleton control. Such a model must be calibrated to each user according to subject-specific musculoskeletal properties and lifting technique variability through several calibration tasks. Given that an extensive calibration limits the practical feasibility of implementing this approach in the workspace, we aimed to optimize the calibration for obtaining appropriate predictive accuracy during work-related tasks, i.e., symmetric lifting from the ground, box stacking, lifting from a shelf, and pulling\/pushing. The root-mean-square error (RMSE) of prediction for the extensive calibration was 21.9 nm (9% of peak moment) and increased up to 35.0 nm for limited calibrations. The results suggest that a set of three optimally selected calibration trials suffice to approach the extensive calibration accuracy. An optimal calibration set should cover each extreme of the relevant lifting characteristics, i.e., mass lifted, lifting technique, and lifting velocity. The RMSEs for the optimal calibration sets were below 24.8 nm (10% of peak moment), and not substantially different than that of the extensive calibration.<\/jats:p>","DOI":"10.3390\/s22010087","type":"journal-article","created":{"date-parts":[[2021,12,23]],"date-time":"2021-12-23T21:40:21Z","timestamp":1640295621000},"page":"87","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Optimizing Calibration Procedure to Train a Regression-Based Prediction Model of Actively Generated Lumbar Muscle Moments for Exoskeleton Control"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1680-9010","authenticated-orcid":false,"given":"Ali","family":"Tabasi","sequence":"first","affiliation":[{"name":"Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Amsterdam Movement Sciences, 1081BT Amsterdam, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1548-7005","authenticated-orcid":false,"given":"Maria","family":"Lazzaroni","sequence":"additional","affiliation":[{"name":"Department of Advanced Robotics, Istituto Italiano di Tecnologia, 16163 Genova, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7613-9947","authenticated-orcid":false,"given":"Niels P.","family":"Brouwer","sequence":"additional","affiliation":[{"name":"Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Amsterdam Movement Sciences, 1081BT Amsterdam, The Netherlands"}]},{"given":"Idsart","family":"Kingma","sequence":"additional","affiliation":[{"name":"Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Amsterdam Movement Sciences, 1081BT Amsterdam, The Netherlands"}]},{"given":"Wietse","family":"van Dijk","sequence":"additional","affiliation":[{"name":"TNO, 2316ZL Leiden, The Netherlands"}]},{"given":"Michiel P.","family":"de Looze","sequence":"additional","affiliation":[{"name":"TNO, 2316ZL Leiden, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6104-7385","authenticated-orcid":false,"given":"Stefano","family":"Toxiri","sequence":"additional","affiliation":[{"name":"Department of Advanced Robotics, Istituto Italiano di Tecnologia, 16163 Genova, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9475-1945","authenticated-orcid":false,"given":"Jes\u00fas","family":"Ortiz","sequence":"additional","affiliation":[{"name":"Department of Advanced Robotics, Istituto Italiano di Tecnologia, 16163 Genova, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7719-5585","authenticated-orcid":false,"given":"Jaap H.","family":"van Die\u00ebn","sequence":"additional","affiliation":[{"name":"Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Amsterdam Movement Sciences, 1081BT Amsterdam, The Netherlands"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1136\/oemed-2014-102346","article-title":"The effect of lifting during work on low back pain: A health impact assessment based on a meta-analysis","volume":"71","author":"Coenen","year":"2014","journal-title":"Occup. 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